Applying deep learning to predict and mitigate adverse environmental conditions in fish aquaculture pens

Fish farms (Aquaculture) produce a large and growing share of seafood in Canada, 29% by value and 19% by production. Worldwide, aquaculture now surpasses wild fish catch. We need aquaculture to be safer for the environment, low cost and yield more fish to feed a growing population in the face of climate change. A key driver of fish health, fish growth, and fish feeding activity is a healthy environment, often measured by dissolved oxygen in water.

Route choice, passage success, and migration survival of Atlantic Salmon (Salmo salar) smolt through the White Rock Hydropower Generating Station and Gaspereau River, Nova Scotia.

In collaboration with Acadia University and Nova Scotia Power, Innovasea inc. proposes an intern to determine route choice, and measure survival of Atlantic salmon smolt as they descend the Gaspereau River past the White Rock Hydropower Generating Station. This project will be completed in full collaboration with Fisheries and Oceans Canada Scientists. The results will both test new V3 tagging technology and inform mitigation efforts that will reduce negative impacts of dam passage on inner Bay of Fundy Atlantic salmon as they begin their migratory journey to the ocean.

A lab-on-chip fish welfare sensor for application in aquaculture

We propose using the Cortisol hormone, secreted from the fishes during stressful events, to provide ongoing monitoring of fish welfare while in their habitats. Instrumented aquaculture pens will allow operators to continuously be aware of threats to fish health, including harmful blooms, predators, and/or poachers. As Canadian aquaculture capital investments are remote and offshore, a low-cost and low-maintenance Cortisol sensor would be ideal for these sites.

Integrating multiple deep learning models to track and classify at-risk fish species near commercial infrastructure

Companies must not harm species at risk around their fixed infrastructure and need a way to detect and monitor at risk fish. However, a species at risk cannot be tagged and studied using conventional surgically implanted fish tracking technology. Innovasea is therefore developing a platform to monitor fish using a combination of sensors such as acoustic devices, visual and active sonar and optical cameras. This effort requires a robust accurate method to detect fish and classify them by species.

Identification of high-frequency periodic acoustic fish tags with deep learning

Innovasea produces fish tags and receivers to track the presence and motion of fish and marine mammals while underwater. Fish tracking (acoustic telemetry) is used by researchers worldwide to determine the abundance and habits of marine life, make decisions about fishing seasons and allowed catches, and help protect marine mammals. Innovasea has developed a novel high-frequency tag technology that is suitable for very small fish and generates more precise trajectories.